With recent advancements in the field of Artificial Intelligence and Machine Learning (AI/ML), the way we write software is transitioning from traditional software methodologies to AI/ML-enabled approaches. This transition brings additional software architecture challenges. The data- and model-centric focus of the AI/ML-enabled systems leads to architectural challenges around data quality, data governance, security, privacy, the design of suitable data pipelines, training infrastructure, real- time inference, model performance, and scalability. Moreover, the randomness during model training, uncertainty in outputs, concept drifts impact the AI/ML life cycle management. Furthermore, industrial AI presents stringent requirements and challenges around safety, cyber security, reliability, interoperability and regulatory compliance. Hence, much remains to be researched towards modelling, evaluation, design decisions, architectural patterns, tactics, evolution and documentation for such AI/ML-enabled software. To facilitate the research in these emerging topics of AI/ML-based software products development, the proposed tech briefing aims to bring together researchers in software architecture with researchers and practitioners specializing in applications of AI/ML to catalyze work at this interface. Given that a significant number of future software products will be AI/ML-driven, a significant fraction of attendees at ISEC will find this tech briefing to be highly relevant.